Abstract
ABSTRACT
Introduction
We codesigned an intervention with a low-resourced community with the aim to investigate the effects of time-restricted eating (TRE) on changes in body weight and associated cardiometabolic outcomes in South African women living with overweight/obesity and HIV who have initiated dolutegravir (DTG)-based antiretroviral therapy (ART).
Methods and analysis
Women with overweight or obesity (body mass index ≥25 kg/m², no upper limit), aged 20–45 years, living with HIV and in a low-resourced community, and receiving DTG-based ART for less than 2 years will be recruited from a community healthcare centre in Khayelitsha, Cape Town (n=152). Participants will be randomised 1:1 to the TRE group (n=76) or standard of care control group (n=76) for 12 months. The TRE group will be required to restrict their eating window to ~8–10 hours/day and will receive nutritional information sessions at baseline and at 3, 6, 9 and 12 months. The primary outcome of body weight will be assessed at baseline and monthly. Cardiometabolic measures will be reported as secondary outcomes. At baseline, 6- and 12 months, an oral glucose tolerance test (to estimate insulin sensitivity and beta-cell function), questionnaires (sociodemographic, food insecurity, quality of life, social support and sleep quality) and a quantified food frequency questionnaire (total energy and macronutrient composition) will be completed. Every 3 months, appetite ratings, bioelectrical impedance (fat mass and fat-free mass), fasting venous bloods (glucose, insulin, gut hormones and systemic inflammation) and process evaluation (qualitative interviews) will be completed. Monthly monitoring will also include anthropometry and blood pressure.
Ethics and dissemination
The study is conducted in accordance with the Declaration of Helsinki and has been approved by the Human Research Ethics Committee of the University of Cape Town (628/2021). Verbal and written consent is required from study participants. Results of this study will be published in peer-reviewed journals and presented at conferences.
Trial registration number
PACTR202302484999720.
Keywords: Obesity, Diabetes & endocrinology, NUTRITION & DIETETICS
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The addition of dietary educational materials empowers women to make more informed decisions on managing their lifestyle behaviours.
The outcomes of this study will inform future recommendations and lifestyle interventions for low-resourced communities in South Africa and other countries in sub-Saharan Africa to combat the increasing prevalence of obesity and type 2 diabetes.
Weight and body mass index do not distinguish between fat and lean mass and interpreting effects of time-restricted eating (TRE) on weight alone as the primary outcome has limitations.
Applying a personalised TRE window of 8–10 hours was intended to accommodate the baseline variability in participant eating windows and this can introduce variability in individual responsiveness to the intervention.
The duration of dolutegravir treatment and HIV is highly variable in the community, and this could cause variability in response to TRE.
Introduction
By 2045, Africa is expected to experience the most significant increase in type 2 diabetes (T2D) globally, with a predicted rise to 55 million, an increase of 134%.1 South Africa is reporting one of the highest prevalence of T2D within the African region, and is the primary cause of death in women, accounting for 7.2% of reported deaths.1 2 South Africa faces an added challenge as it bears the highest global burden of HIV infection (7.7 million people), of which women are disproportionally affected.3 In 2019, the WHO recommended dolutegravir (DTG) in combination with a nucleoside reverse-transcriptase inhibitor backbone to be used as the preferred first-line regimen for people living with HIV.4 However, when switching from efavirenz (EFV)-based regimes (Tenofovir Disoproxil Fumarate [TDF]/Emtricitabine [FTC]/EFV) to DTG-based regime (TDF/Lamivudine [3TC]/DTG) there was a median weight increase of 2.9 kg,5 with a more significant increase in weight shown in antiretroviral therapy (ART)-naïve patients initiating a DTG-based regime.6 The question of whether the weight gain represents a ‘return to health’ or is a result of an ART regimen is a subject of ongoing debate. Accordingly, interventions may be required to focus on managing body weight in people living with HIV (PLWH), especially when initiating DTG-based treatment.
The translation of effective lifestyle interventions in high-income countries to programmes in resource-limited communities presents a significant challenge. Accordingly, it is important to develop and evaluate culturally appropriate lifestyle interventions that are low cost, effective and sustainable,7 with very little data on simple interventions promoting weight maintenance or weight loss in South Africa.8 9 When implementing lifestyle interventions in resource-poor communities, there are many barriers at both a systemic level (low-quality healthcare, urbanisation and population changes) and personal level (poverty, food insecurity, education and disease perception).10 Notably, lifestyle interventions aimed at the treatment of obesity and prevention of T2D in Africa are scarce and do not initiate the formative codesign research phases that may help with programme implementation and sustainability.
Dietary strategies are difficult to implement in resource-poor settings such as South Africa due to widespread food insecurity. In 2021, 35% of households reported not having enough money for food in the past month and 16% reported household hunger in the past month.11 In contrast to traditional dietary interventions, time-restricted eating (TRE) does not require participants to eat specific foods, but rather to restrict their eating window to ~8–10 hours in the day.12,17 TRE has been suggested as a feasible strategy to reduce body weight and improve cardiometabolic health in individuals with overweight and obesity.15 18 19 TRE (eating window of 4–10 hours/day) has become widely studied in developed countries with positive results in response to a spectrum of chronic diseases,12 14 15 18 19 but recent data have shown no clinically relevant effects on body weight following 3 months of 10 hours/day TRE.16 It is imperative that local data is generated to understand and identify appropriate methods for weight loss and weight maintenance in this high-risk and understudied population. The present study combines knowledge and experience from the needs assessment and pilot study phases of the project that were used to codesign this randomised controlled trial (RCT) and ensure successful implementation and sustainability within the community.20 We hypothesise that an 8–10 hours/day TRE intervention will be a strategy to prevent weight gain in women at high risk of cardiometabolic disease.21 We aimed to investigate the effects of TRE on changes in body weight and associated cardiometabolic outcomes in South African women living with overweight/obesity and HIV receiving DTG-based ART.
Methods and analysis
Study design
In this RCT, women with overweight or obesity, living with HIV and in a low-resourced community, and receiving a DTG-based regimen will be randomised into TRE (intervention) or standard of care (control) for 12 months (48 weeks). Figure 1 shows the research process that consists of two phases: (1) the completed formative assessment phase and (2) the RCT. The formative phase consisted of the needs assessment and pilot study that were used to inform and codesign the RCT.20 22 Main recommendations from the participants, implications for the RCT and rationale are provided in table 1. The primary aim is to investigate changes in body weight over the 12-month intervention between intervention and control groups. The secondary aim is to assess changes over 12 months in outcome measures relating to cardiometabolic risk. Secondary outcome measures include fasting glucose, insulin and HbA1c, estimated insulin sensitivity and secretion, blood pressure and resting heart rate, perceived appetite and hunger, body composition, systemic inflammation and appetite hormones, dietary intake, sleep quality, physical activity, TRE compliance, sociodemographic characteristics, food insecurity, medical and family history, quality of life and self-efficacy, and qualitative process evaluation (table 2).
Figure 1. Overview and design of the research process. Interviews for the formative stages were analysed using models related to behaviour change that can advise on the implementation of the randomised controlled trial (RCT). (1) The needs assessment and pilot time-restricted eating (TRE) were assessed using focus group interviews and key informant interviews that were structured and analysed using the COM-B model. Capability, Opportunity, and Motivation (COM-B) are identified as the three key factors capable of changing behaviour at a system, service provider and patient level. (2) Theoretical domains framework (TDF) to help identify and describe barriers and facilitators that influence behaviour (20).
Table 1. Summary of the findings from the previously published formative assessment phase to inform and codesign the RCT.
| Formative assessment phase findings | Implications for the RCT | Rationale |
| Difficulty recruiting men. | Only include women in the RCT. | The recruitment of men was difficult as most men attending the clinic had a BMI<25 kg/m2 and were less willing to participate in the study.49 50T2D is the leading cause of death in South African women, and the HIV peak prevalence (39.4% vs 24.8%) and overweight/obesity (68% vs 31%) are higher in women compared with men.21 |
| Dietary education sessions recommended by participants. | Include dietary education sessions. | Improve adherence to RCT and sustainability. |
| Support throughout the TRE programme recommended by participants. | Support throughout the intervention in the form of calls and text messages.Recording daily eating window in calendar. | Improve adherence to RCT. Calendar can be used to record daily compliance. |
BMIbody mass indexRCTrandomised controlled trialT2Dtype 2 diabetesTREtime-restricted eating
Table 2. Overview of measures and testing schedule.
| Baseline (0) | Monthly | Weekly | 3 months(12 weeks) | 6 months(24 weeks) | 9 months(36 weeks) | 12 months(48 weeks) |
| Questionnaires | ||||||
| Sociodemographic | x | x | x | |||
| Medical history and medication use | x | x | ||||
| Quality of life (EQ-5D) | x | x | x | |||
| Pittsburgh Sleep Quality Index (PSQI) | x | x | x | |||
| Global Physical Activity Questionnaire (GPAQ) | x | x | x | |||
| Household Food Insecurity Access Scale (HFIAS) | x | x | x | |||
| Social support | x | x | x | x | x | |
| Quantified food frequency | x | x | x | |||
| Appetite VAS | x | x | x | x | x | |
| Habitual eating window | x | |||||
| Body composition | ||||||
| Body weight | x | x | x | x | x | x |
| Anthropometry | x | x | x | x | x | |
| Bioelectrical impedance | x | x | x | x | x | |
| Cardiometabolic risk | ||||||
| Fasting venous blood | x | x | x | x | x | |
| Oral glucose tolerance test | x | x | x | |||
| Blood pressure | x | x | x | x | x | x |
| Qualitative assessment | ||||||
| Process evaluation—structured interviews | x | x | x | x | ||
| TRE group only | ||||||
| Text message or phone calls | x | x | ||||
| Calendar (daily eating window compliance) | x | |||||
| Education session | x | x | x | x | x |
EQ-5DEuroQol 5 DimensionVASvisual analogue scale
Population, recruitment and screening
The project will be conducted in partnership with the Ubuntu ART Clinic at Site B Community Health Centre in Khayelitsha, which monitors ~12 500 patients on ART. Khayelitsha is a large, periurban informal settlement in Cape Town, South Africa, of which 99% are black South African and isiXhosa speaking.23 Participants will be recruited during one of their routine clinic visits and will return to the clinic to complete the screening process. During screening, each participant will be provided a detailed description of the study by an isiXhosa-speaking research assistant and asked to sign a formal verbal and written consent (online supplemental material—participant information and consent form). Women (n=152) will be randomised (1:1) using REDCap into the intervention (n=76) or standard of care control group (n=76). All data will be collected and stored using REDCap electronic data capture tools hosted by the University of Cape Town (UCT).24 25 Participants will be enrolled in the study for 12 months (48 weeks) and both groups will receive standard of care during their regular visits to the clinic. Monthly measures will be completed at the resource-limited Ubuntu ART Clinic in Khayelitsha, while three monthly visits will be completed at the UCT.
An overview of the testing schedule is shown in table 2. The study is conducted in accordance with the Declaration of Helsinki and has been approved by the Human Research Ethics Committee of the UCT (628/2021). Clinical trial registration was approved by Pan African Clinical Trials Registry in February 2023 (www.pactr.org; PACTR202302484999720). Participant enrolment for the RCT occurred between April and December 2023. Study completion as the final 1-year follow-up will occur in December 2024.
Inclusion and exclusion criteria
Eligible women, aged 20–45 years, living with HIV and in a low-resourced community, and having a body mass index (BMI) of ≥25 kg/m² (no upper limit) will be recruited from the Ubuntu ART Clinic in Khayelitsha, Cape Town. They should be on DTG for 1–24 months. Participants are excluded if they have active or unstable medical conditions affecting body weight or glycaemic control, severe eating disorders, significant psychiatric illnesses, inflammatory bowel disease, malabsorption-related disorders, known active tuberculosis, helminth infection, hepatitis, alcohol/drug addiction, pregnant, breastfeeding or planning pregnancy within a year, postmenopausal, recent positive COVID-19 tests or current COVID-19 symptoms, over 5% weight loss during the last 6 months, use of medications such as glucocorticoids, hydrochlorothiazide and beta-blockers, and concurrent involvement in another intervention study.
Intervention group: TRE and education
Based on previously reported protocol for TRE,26 participants in the intervention group will (1) self-implement TRE on a daily basis, (2) receive nutritional information sessions at baseline and 3, 6, 9 and 12 months and (3) continue their DTG-based ART and receive standard of care during their regular visits to the clinic. The TRE component advises participants to eat within the same time window (including foods/snacks and beverages, except for water) each day. Specifically, TRE is an eating pattern that focuses on the timing of eating. To personalise the eating window for each participant, we will use their baseline habitual eating window as reference. This was restricted to a ‘daily’ eating window (starting in the morning and finishing in the evening). The goal is to establish an eating window of 8–10 hours, typically reducing their habitual eating window by 4 hours. The eating window of 8–10 hours was selected to accommodate for variability in participants’ baseline eating windows, noting that interventions commonly select an 8-hour eating window.12,1417 Within the first 4 weeks of TRE, participants are allowed to alter their eating window to ensure continued compliance and sustainability. During the eating window, the type or quantity of food consumed is not restricted. Outside their selected eating window, participants can only consume water, black tea or coffee, with no sweeteners, sugar or milk.
Adherence to TRE will be monitored via a paper-based calendar, on which the participants will document their eating window each day. The calendar will be returned at each monthly visit. The participants will receive a weekly alternating phone call or text message to assist with adherence to the intervention. The phone calls will provide the participants the opportunity to discuss difficulties and changes in their eating window if required within the first month. Text messages are aimed to provide encouragement and motivation. Adherence to the intervention is calculated as number/percentage of days during the intervention that the participants follow their selected eating window. Per protocol adherence is defined as ≥80% compliance.
The dietary education sessions have been developed by a dietitian, with the baseline session mainly dedicated to information and guidance on TRE. The remaining education sessions will be aligned with the evidence-based South African Food Based Dietary Guidelines (SAFBDGs) and the food guide.27 The motivation for the decision to use the SAFBDGs and Guide is as follows: (1) The guidelines have been specifically developed for the South African population taking into consideration food availability and cultural acceptability. (2) It is health promoting and contributes to the prevention of lifestyle-related chronic diseases. The SAFBDGs were developed following the guidance provided by the WHO and the Food and Agriculture Organisation.28 The SAFBDGs provide actions considered to be achievable, affordable and sustainable which can be performed by the South African population.27 The dietary education sessions will ensure the concept of TRE is firmly understood, including managing the timing of medication when following TRE, coping strategies to manage social barriers and emotional eating and common myths regarding healthy eating. An outline of the sessions and the handouts is provided in table 3.
Table 3. Outline of the dietary education sessions and handouts for the TRE group.
| Information session | Content to be covered | Handout |
| Baseline | Explanation of what TRE entails and what is expected from participants.Managing medication timing when following TRE.Coping strategies to combat emotional eating and the home or social environment.Speaking with family and friends about TRE. |
|
| 3 months | Summary of the South African Food-Based Dietary Guidelines.Healthy food choices for meals and snacks. |
|
| 6 months | Portion control using the plate and hand model.Awareness of the sugar content in drinks. |
|
| 9 months | Healthy eating does not have to be expensive.Tips to save money when buying groceries.Myths and facts about healthy eating. |
|
TREtime-restricted eating
Control group: standard of care
The control group will continue their DTG-based ART and will receive standard of care during their regular visits to the clinic. The standard of care includes the HIV support groups that are managed in the clinic. These groups include scheduled two monthly visits to the clinic to collect medications and a consultation with an HIV counsellor who collects body weight and addresses ART compliance. Patients are referred to the consulting clinicians if compliance issues or illnesses are present. They will attend all testing sessions but will not receive any intervention or weekly monitoring/contact. The control group will be asked to continue their habitual daily activities and eating patterns and will be provided with all dietary education material following the completion of the study.
Testing measures and procedures
Table 2 shows a timeline for all testing measures and procedures. At baseline, 6- and 12 months, an oral glucose tolerance test (OGTT; to estimate insulin sensitivity and beta-cell function), questionnaires (sociodemographic, food insecurity, quality of life, social support and sleep quality) and a quantified food frequency questionnaire (qFFQ; total energy and macronutrient composition) will be completed. Every 3 months, appetite ratings, social support questionnaire, bioelectrical impedance (fat mass and fat-free mass), fasting venous bloods (glucose, insulin, gut hormones and systemic inflammation) and process evaluation (qualitative interviews) will be completed. Monthly monitoring will include body weight and blood pressure.
Body composition assessment
Body mass (Omron HN 300-T, Kyoto, Japan) and stature (3PHTROD-WM, Detecto, Missouri, USA) will be measured in lightweight clothing for the calculation of BMI and reported as kg/m2. Waist circumference (mid-way between the lowest rib and iliac crest) and hip circumference (largest protrusion of the buttocks) will be measured with a metal tape and the average of two measures will be reported, or the median of three measurements reported if a large discrepancy (>1%) is evident between the first two measures.29 Weight and anthropometry collected every 3 months are completed following an overnight fast (10–12 hours), while monthly measures are completed in the Ubuntu Clinic at a time convenient for the participant. A single-frequency (50 kHz) bioelectrical impedance analyser (BIA-101Q; RLJ Systems, Clinton Township, Michigan, USA) will be used to estimate total body fat mass (reported as % and kg) and fat-free mass (kg) using a population-specific formula.30
Questionnaires
Habitual eating window: This was assessed at baseline using a recall of eating windows (start and stop times) in the previous 7 days.
Sociodemographic and medical history: This questionnaire includes measures of socioeconomic status based on factors such as asset index, education, housing and housing density, food security (Household Food Insecurity Access Scale),31 employment, and medical history of disease and medication use.
Quality of life and physical behaviours: The participants will complete a quality of life (EuroQol 5 Dimension) questionnaire, Pittsburgh Sleep Quality Index32 and Global Physical Activity Questionnaire.33 34
Social support and appetite: Participants will complete a social (family and friends) support questionnaire.35 The appetite visual analogue scales will be completed when fasting and will be used to assess appetite using measures relating to hunger, satiety, fullness, thirst, estimated prospective food consumption, and desire for sweet, salt, and fat, and potential nausea.36
Dietary intake assessment: Consideration of the target population, respondent burden and expertise in the quantification of usual intake of total energy and nutrients is feasible when using an interviewer-conducted qFFQ, initially developed for use in South Africa.37,39 The qFFQ was adapted by the two dietitians to assess the intake of participants with a similar cultural and socioeconomic background. This rigorous iterative process will assess a recall period of the past week (7 days). Trained interviewers use photographs of food items to assist with participant recall. The participants are asked to estimate their habitual intake by selecting the most accurate representation of their portion size from either two-dimensional actual size drawings of foods, household utensils or three-dimensional validated food models. Daily macronutrient and micronutrient intakes will be calculated by multiplying the frequency of intake by the nutrient composition specified for each food item and its portion weight, using the software program FoodFinder III, supplied by the Nutrition Intervention Research Unit (South African Medical Research Council (SAMRC), Parow, South Africa).
Fasting blood sampling and OGTT
Following an overnight fast (10–12 hours), fasting duration will be reported and venous blood samples will be drawn for the measurement of glycated haemoglobin A1c (HbA1c), haemoglobin, glucose, insulin, systemic inflammation (eg, C reactive protein), lipid profile (total cholesterol, high-density lipoprotein (HDL)-cholesterol and triglycerides) and gut hormones (eg, ghrelin, glucagon-like peptide-1, glucose-dependent insulinotropic polypeptide, peptide YY). Serum low-density lipoprotein cholesterol concentrations will be estimated using the Friedewald equation.40 Participants will then complete an OGTT and will ingest 75 g of glucose dissolved in 250 mL of water over a 5 min period. Blood samples for the analysis of glucose and insulin will be drawn at 30 and 120 min after glucose ingestion. All blood samples will be collected in EDTA, sodium fluoride and potassium oxalate, and serum seperator tubes (SST). Samples will be centrifuged at 3000 rpm for 10 min at 4°C. Plasma and serum will be used for the immediate analysis (Cobas c 311 analyser, Roche Diagnostics, Midrand, South Africa) of glucose (enzymatic assay reference method with hexokinase), insulin (immunoassay, sandwich principle with two human insulin monoclonal antibodies), HbA1c (turbidimetric inhibition immunoassay for haemolysed whole blood) and lipid profile (enzymatic colorimetric test for analysis of triglycerides, total cholesterol and HDL-cholesterol). The remaining samples will be stored at −80°C until further analyses.
Homeostasis model assessment–insulin resistance is calculated from fasting glucose and insulin concentrations,41 42 and Matsuda index, as an estimate of peripheral insulin sensitivity is calculated from the OGTT (0, 30 and 120 min).43 Insulin response is estimated using the insulinogenic index (IGI, ΔInsulin30 min-0 min/ΔGlucose30 min-0 min)44 and disposition index, as an estimate of beta cell function is calculated using the ratio of IGI to insulin sensitivity.45 46
Blood pressure
The participant will be seated (rested) for 15 min. Blood pressure and resting heart rate will then be measured three times with 1 min intervals using an appropriately sized cuff and an automated blood pressure monitor (Omron EVOLV, Kyoto, Japan). The average of the final two measurements for systolic and diastolic blood pressure will be reported.
Monitoring and compliance
To assist with the monitoring and compliance of ART throughout the intervention, we will obtain routinely collected medical information using the patient medical record system. This detail will include variables relating to currently prescribed medications, and routine bloods such as viral load and CD4 count.
Process evaluation: Completed with participants every 3 months (3, 6, 9 and 12 months) and at the end of the intervention, research assistants and managers will be asked to participate. This process will be used to understand the barriers and facilitators of TRE for sustainability in a low-resourced setting. This will include conducting structured informal key informant interviews either in person or on the telephone, with an anticipated duration of 30 min. The interviews will target participants who have dropped out, and those who have remained within the intervention. The research staff members (clinical research assistants, clinical trial nurse and project managers) who have been involved in the running of the trial will also be interviewed. All participants who drop out will be contacted over the phone to request a time to complete a telephonic interview. This process will include questions designed to understand the barriers and facilitators to recruitment, attrition, behaviour change, contextual factors and fidelity of intervention implementation.47
Statistical and data analyses
Quantitative analyses
Sample size calculation was completed based on a power of 80%, a standardised mean difference of 0.5 between the two groups (medium effect size), α=0.05 requires a sample size of 128 (64 per group), but with an expected dropout rate of 20%, we will include 152 individuals (76 in the TRE intervention group and 76 in the control group) in the RCT. A recent 12 month RCT showed a −3.49 (95% CI −5.65 to −1.32; 5.63 (SD)) kg change in weight in TRE group compared non-interventional control of 1.12 (95% CI −0.69 to 2.94; 4.72 (SD)) kg.15 This equates to a difference between groups of −4.61 (95% CI −7.37 to −1.85) or a large, estimated effect size (Cohen’s d) of 0.887. Using this effect size, a total sample size of 44 (22 per group) will achieve 80% power, 58 (29 per group) will achieve 90% power and 70 (35 per group) will achieve 95% power. Statistical analyses will be performed before unblinding the interventions using an intention-to-treat analysis. A per protocol analysis will also be performed to include only participants who adhered to TRE (≥80% compliance). Data will be processed and presented with the use of standard descriptive statistics. Comparisons between groups will be performed using mixed-effects models to explore group by time interactions and main effects of time and group. The mixed model is appropriate for handling missing at random data without removing the participant from the analyses. Potential covariates will be explored and considered in the model. These may include, but not limited to, age, socioeconomic status, social support, household food insecurity, physical activity, adherence, and DTG and HIV duration.
Qualitative analyses
Key informant interviews will be conducted in isiXhosa, audio recorded, translated and transcribed into English, and analysed using NVivo qualitative data analysis software (V.14, QSR International, Melbourne, Australia). An iterative approach to thematic analysis will be implemented and will include data familiarisation, coding, developing a thematic framework, reviewing, and defining themes and interpretation.48 Themes will be inductively identified.
Data monitoring and sharing
Data generated from the trial will be stored in a computer database in a secure facility, and in a manner that maintains participants’ confidentiality. The data collected will be managed by the principal investigators and shared with other researchers in the future according to the policies governing data sharing and preservation by the SAMRC and UCT. The principal investigators are prepared to share the dataset with the wider scientific community and will make the data available after all the results have been published, in response to appropriate requests. As there are no proprietary or patentable data generated by the study, there will be no restrictions on data sharing.
Patient and public involvement
The formative work used to design the RCT consisted of a needs assessment and pilot trial for feasibility and design recommendations from participants (figure 1 and table 1). Participants were not involved in implementing the RCT, but dissemination of results will occur following the completion of the trial. Outcomes will be disseminated to all participants and their families, and staff members (nurses, HIV counsellors, doctors) working in the Ubuntu Clinic.
Ethics and dissemination
The study is conducted in accordance with the Declaration of Helsinki and has been approved by the Human Research Ethics Committee of the UCT (628/2021). Clinical trial registration was approved by Pan African Clinical Trials Registry in February 2023 (www.pactr.org; PACTR202302484999720). Participant enrolment for the RCT occurred between April and December 2023. Study completion as the final 1-year follow-up will occur in December 2024. Results of this study will be published in peer-reviewed journals and presented at conferences. Research translation is a key focus for all phases of this project, and at the end of this project the anticipated outcomes achieved will be:
Creating a community-based codesign and evaluation framework that is culturally appropriate and suitable for large-scale implementation of TRE within low-resourced communities.
Providing exposure to dietary educational materials to empower women to make more informed decisions on managing their lifestyle behaviours.
The outcome of the present study will be used to inform future recommendations and lifestyle interventions in South Africa as well as other countries in sub-Saharan Africa to combat the increasing prevalence of obesity and T2D.
supplementary material
Footnotes
Funding: National Research Fund (grant number 141970) and European Foundation for the Study of Diabetes (EFSD) and Lilly Exploring and Applying New Strategies in Diabetes (EXPAND) Programme 2020.
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2024-086203).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Consent obtained directly from patient(s)
Patient and public involvement: Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Contributor Information
Amy E Mendham, Email: amy.mendham@sa.gov.au.
Julia H Goedecke, Email: julia.goedecke@mrc.ac.za.
Lorena Heckens, Email: heckenslorena@gmail.com.
Fatima Hoosen, Email: fatima.hoosen@uct.ac.za.
Majken Lillholm Pico, Email: majken.lillholm.pico@regionh.dk.
Andre P Kengne, Email: Andre.Kengne@mrc.ac.za.
Dirk L Christensen, Email: dirklc@sund.ku.dk.
Ole F Olesen, Email: olesen@sund.ku.dk.
Jonas Salling Quist, Email: jonas.salling.quist@regionh.dk.
Joel Dave, Email: joeldave@endocrine.co.za.
Kristine Færch, Email: KRIF@novonordisk.com.
Louise Groth Grunnet, Email: Louise.groth.grunnet.02@regionh.dk.
References
- 1.Magliano DJ, Boyko EJ. IDF diabetes atlas. 10th. 2022. edn. [Google Scholar]
- 2.Africa SS Mortality and causes of death in South Africa: findings from death notification: statistics South Africa. 2018
- 3.UNAIDS AIDS statistics—2020 fact sheet; 2020. 2021
- 4.World Health Organisation Consolidated guidelines on HIV prevention, testing, treatment, service delivery and monitoring: recommendations for a public health approach. 2021 [PubMed]
- 5.Bosch B, Akpomiemie G, Chandiwana N, et al. Weight and Metabolic Changes After Switching From Tenofovir Alafenamide/Emtricitabine (FTC)+Dolutegravir (DTG), Tenofovir Disoproxil Fumarate (TDF)/FTC + DTG, and TDF/FTC/Efavirenz to TDF/Lamivudine/DTG. Clin Infect Dis. 2023;76:1492–5. doi: 10.1093/cid/ciac949. [DOI] [PubMed] [Google Scholar]
- 6.Venter WDF, Moorhouse M, Sokhela S, et al. Dolutegravir plus Two Different Prodrugs of Tenofovir to Treat HIV. N Engl J Med. 2019;381:803–15. doi: 10.1056/NEJMoa1902824. [DOI] [PubMed] [Google Scholar]
- 7.Fitch KV. Contemporary Lifestyle Modification Interventions to Improve Metabolic Comorbidities in HIV. Curr HIV/AIDS Rep . 2019;16:482–91. doi: 10.1007/s11904-019-00467-0. [DOI] [PubMed] [Google Scholar]
- 8.Goedecke JH, Mendham AE. Pathophysiology of type 2 diabetes in sub-Saharan Africans. Diabetologia. 2022;65:1967–80. doi: 10.1007/s00125-022-05795-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Fortuin-de Smidt MC, Mendham AE, Hauksson J, et al. Effect of exercise training on insulin sensitivity, hyperinsulinemia and ectopic fat in black South African women: a randomized controlled trial. Eur J Endocrinol. 2020;183:51–61. doi: 10.1530/EJE-19-0957. [DOI] [PubMed] [Google Scholar]
- 10.Bekele H, Asefa A, Getachew B, et al. Barriers and Strategies to Lifestyle and Dietary Pattern Interventions for Prevention and Management of TYPE-2 Diabetes in Africa, Systematic Review. J Diabetes Res. 2020;2020:7948712. doi: 10.1155/2020/7948712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.van der Berg S, Patel L, Bridgman G. Food insecurity in South Africa: Evidence from NIDS-CRAM wave 5. Dev South Afr. 2022;39:722–37. doi: 10.1080/0376835X.2022.2062299. [DOI] [Google Scholar]
- 12.Dote-Montero M, Sanchez-Delgado G, Ravussin E. Effects of Intermittent Fasting on Cardiometabolic Health: An Energy Metabolism Perspective. Nutrients. 2022;14:489. doi: 10.3390/nu14030489. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Dote-Montero M, Merchan-Ramirez E, Oses M, et al. Efficacy of different 8 h time-restricted eating schedules on visceral adipose tissue and cardiometabolic health: A study protocol. Nutr Metab Cardiovasc Dis. 2024;34:177–87. doi: 10.1016/j.numecd.2023.09.014. [DOI] [PubMed] [Google Scholar]
- 14.Varady KA, Cienfuegos S, Ezpeleta M, et al. Clinical application of intermittent fasting for weight loss: progress and future directions. Nat Rev Endocrinol. 2022;18:309–21. doi: 10.1038/s41574-022-00638-x. [DOI] [PubMed] [Google Scholar]
- 15.Lin S, Cienfuegos S, Ezpeleta M, et al. Time-Restricted Eating Without Calorie Counting for Weight Loss in a Racially Diverse Population : A Randomized Controlled Trial. Ann Intern Med. 2023;176:885–95. doi: 10.7326/M23-0052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Quist JS, Pedersen HE, Jensen MM, et al. Effects of 3 months of 10-h per-day time-restricted eating and 3 months of follow-up on bodyweight and cardiometabolic health in Danish individuals at high risk of type 2 diabetes: the RESET single-centre, parallel, superiority, open-label, randomised controlled trial. Lancet Healthy Longev. 2024;5:e314–25. doi: 10.1016/S2666-7568(24)00028-X. [DOI] [PubMed] [Google Scholar]
- 17.Domaszewski P, Konieczny M, Dybek T, et al. Comparison of the effects of six-week time-restricted eating on weight loss, body composition, and visceral fat in overweight older men and women. Exp Gerontol. 2023;174:112116. doi: 10.1016/j.exger.2023.112116. [DOI] [PubMed] [Google Scholar]
- 18.Moon S, Kang J, Kim SH, et al. Beneficial Effects of Time-Restricted Eating on Metabolic Diseases: A Systemic Review and Meta-Analysis. Nutrients. 2020;12:1267. doi: 10.3390/nu12051267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.de Cabo R, Mattson MP. Effects of Intermittent Fasting on Health, Aging, and Disease. N Engl J Med. 2019;381:2541–51. doi: 10.1056/NEJMra1905136. [DOI] [PubMed] [Google Scholar]
- 20.Hoosen F, Pico ML, Goedecke JH, et al. Development and feasibility testing of a time-restricted eating intervention for women living with overweight/obesity and HIV in a resource-limited setting of South Africa. BMC Public Health. 2024;24:2768. doi: 10.1186/s12889-024-20228-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.National Department of Health SSA, South African Medical Research Council, ICF . South Africa demographic and health survey 2016: key indicators. South Africa and Rockville, Maryland: NDoH, Stats SA, SAMRC and ICF Pretoria; 2019. [Google Scholar]
- 22.Hempler NF, Bjerre N, Varming AR, et al. Designing a Co-created Intervention to Promote Motivation and Maintenance of Time-Restricted Eating in Individuals With Overweight and Type 2 Diabetes. J Nutr Educ Behav. 2023;55:371–80. doi: 10.1016/j.jneb.2023.03.001. [DOI] [PubMed] [Google Scholar]
- 23.Smit W, de Lannoy A, Dover RVH, et al. Making unhealthy places: The built environment and non-communicable diseases in Khayelitsha, Cape Town. Health & Place . 2016;39:196–203. doi: 10.1016/j.healthplace.2016.04.006. [DOI] [PubMed] [Google Scholar]
- 24.Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95:103208. doi: 10.1016/j.jbi.2019.103208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Quist JS, Jensen MM, Clemmensen KKB, et al. Protocol for a single-centre, parallel-group, randomised, controlled, superiority trial on the effects of time-restricted eating on body weight, behaviour and metabolism in individuals at high risk of type 2 diabetes: the REStricted Eating Time (RESET) study. BMJ Open. 2020;10:e037166. doi: 10.1136/bmjopen-2020-037166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Vorster HH, Badham JB, Venter CS. An introduction to the revised food-based dietary guidelines for South Africa. South Afr J Clin Nutr. 2013;26:S5–12. [Google Scholar]
- 28.World Health Organisation Preparation and use of food-based dietary guidelines: report of a joint FAO/WHO consultation, p. vi, 108-vi. 1998 [PubMed]
- 29.Esparza-Ros F, Vaquero-Cristóbal R, Marfell-Jones M. International standards for anthropometric assessment. International Society for the Advancement of Kinanthropometry (ISAK); 2019. [Google Scholar]
- 30.Luke A, Bovet P, Forrester TE, et al. Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin. Eur J Clin Nutr. 2013;67:956–60. doi: 10.1038/ejcn.2013.123. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Coates J, Swindale A, Bilinsky P. Washington, DC: Food and Nutrition Technical Assistance Project, Academy for Educational Development; 2007. Household food insecurity access scale (HFIAS) for measurement of household food access: indicator guide. Version 3. [Google Scholar]
- 32.Buysse DJ, Reynolds CF, 3rd, Monk TH, et al. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28:193–213. doi: 10.1016/0165-1781(89)90047-4. [DOI] [PubMed] [Google Scholar]
- 33.Armstrong T, Bull F. Development of the World Health Organization Global Physical Activity Questionnaire (GPAQ) J Public Health . 2006;14:66–70. doi: 10.1007/s10389-006-0024-x. [DOI] [Google Scholar]
- 34.Bull FC, Maslin TS, Armstrong T. Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health. 2009;6:790–804. doi: 10.1123/jpah.6.6.790. [DOI] [PubMed] [Google Scholar]
- 35.Sallis JF, Grossman RM, Pinski RB, et al. The development of scales to measure social support for diet and exercise behaviors. Prev Med. 1987;16:825–36. doi: 10.1016/0091-7435(87)90022-3. [DOI] [PubMed] [Google Scholar]
- 36.Flint A, Raben A, Blundell J, et al. Reproducibility, power and validity of visual analogue scales in assessment of appetite sensations in single test meal studies. Int J Obes. 2000;24:38–48. doi: 10.1038/sj.ijo.0801083. [DOI] [PubMed] [Google Scholar]
- 37.Makura-Kankwende CBT, Gradidge PJ, Crowther NJ, et al. Association of Longitudinal Nutrient Patterns with Body Composition in Black Middle-Aged South African Women: A Five-Year Follow-Up Study. Int J Environ Res Public Health. 2022;19:12792. doi: 10.3390/ijerph191912792. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Steyn NP, Senekal M, Norris SA, et al. How well do adolescents determine portion sizes of foods and beverages? Asia Pac J Clin Nutr. 2006;15:35–42.:35. [PMC free article] [PubMed] [Google Scholar]
- 39.Steyn NP, Jaffer N, Nel J, et al. Dietary Intake of the Urban Black Population of Cape Town: The Cardiovascular Risk in Black South Africans (CRIBSA) Study. Nutrients. 2016;8:285. doi: 10.3390/nu8050285. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502. [PubMed] [Google Scholar]
- 41.Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9. doi: 10.1007/BF00280883. [DOI] [PubMed] [Google Scholar]
- 42.Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004;27:1487–95. doi: 10.2337/diacare.27.6.1487. [DOI] [PubMed] [Google Scholar]
- 43.Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22:1462–70. doi: 10.2337/diacare.22.9.1462. [DOI] [PubMed] [Google Scholar]
- 44.Tura A, Kautzky-Willer A, Pacini G. Insulinogenic indices from insulin and C-peptide: comparison of beta-cell function from OGTT and IVGTT. Diabetes Res Clin Pract. 2006;72:298–301. doi: 10.1016/j.diabres.2005.10.005. [DOI] [PubMed] [Google Scholar]
- 45.Kahn SE, Prigeon RL, McCulloch DK, et al. Quantification of the relationship between insulin sensitivity and beta-cell function in human subjects. Evidence for a hyperbolic function. Diabetes. 1993;42:1663–72. doi: 10.2337/diab.42.11.1663. [DOI] [PubMed] [Google Scholar]
- 46.Ahrén B, Pacini G. Importance of quantifying insulin secretion in relation to insulin sensitivity to accurately assess beta cell function in clinical studies. Eur J Endocrinol. 2004;150:97–104. doi: 10.1530/eje.0.1500097. [DOI] [PubMed] [Google Scholar]
- 47.Sharif SMd, Hanson M, Chong DW, et al. Learning from the process evaluation of a complex, pre-conception randomised controlled trial in Malaysia: the Jom Mama project. J Glob Health Rep. 2022;6:e2022025. doi: 10.29392/001c.34228. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Terry G, Hayfield N, Clarke V, et al. Thematic analysis. The SAGE handbook of qualitative research in psychology. 2017;2:17–37. [Google Scholar]
- 49.Kim KB, Shin YA. Males with Obesity and Overweight. J Obes Metab Syndr . 2020;29:18–25. doi: 10.7570/jomes20008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Beia T, Kielmann K, Diaconu K. Changing men or changing health systems? A scoping review of interventions, services and programmes targeting men’s health in sub-Saharan Africa. Int J Equity Health. 2021;20:87. doi: 10.1186/s12939-021-01428-z. [DOI] [PMC free article] [PubMed] [Google Scholar]

